Pandas DataFrame rpow() Method
Example
Find the exponential power of 5 for each value in the DataFrame:
import pandas as pd
data = {
"points": [4, 5,
6],
"total": [10, 12, 15]
}
df = pd.DataFrame(data)
print(df.rpow(5))
Try it Yourself »
Definition and Usage
The rpow() method raises a specified number
with each value in the DataFrame.
This method is called reverse pow, and is similar to the
pow() method, but
instead of calculating 45 it calculates
54.
The specified number must be an object that can be used to raise the values in the DataFrame. It can be a
constant number like the one in the example, or it can be a list-like object
like a list [5, 10] or a tuple
{"points": 5, "total": 10}, or a Pandas
Series or another DataFrame, that fits with the original DataFrame.
Syntax
dataframe.pow(other, axis, level, fill_value)
Parameters
| Parameter | Description |
|---|---|
| other | Required. A number, list of numbers, or another object with a data structure that fits with the original DataFrame. |
| axis | Optional, A definition that decides whether to compare by index or
columns. 0 or 'index' means compare by index. 1 or 'columns' means compare by columns |
| level | Optional. A number or label that indicates where to compare. |
| fill_value | Optional. A number, or None. Specifies what to do with NaN values before doing the calculation. |
Return Value
A DataFrame with the results.